Unmanned aerial vehicle with biometric verification

ABSTRACT

Disclosed herein are system, method, and computer program product embodiments for locating, identifying, and tracking a known criminal, fugitive, missing person, and/or any other person of interest. An embodiment operates by deploying an unmanned aerial vehicle, determining the mode of operation of the UAV, operating the UAV in accordance with the mode of operation of the UAV, determining whether a subject has been detected, capturing a first voice sample associated with the subject, authenticating the identity of the subject, and transmitting the GPS location of the unmanned aerial vehicle to a computing device.

RELATED APPLICATIONS

This application is a continuation of U.S. Nonprovisional patentapplication Ser. No. 14/971,891, filed on Dec. 16, 2015, issued as U.S.Pat. No. 10,579,863 titled “Unmanned Aerial Vehicle With BiometricVerification,” and the contents of which are hereby incorporated hereinby reference in its entirety

FIELD OF THE INVENTION

The present invention relates generally to the field of unmanned aerialvehicle systems used in law enforcement, penal institutions, or similarfacilities. In particular, the present invention relates to an unmannedaerial vehicle in communication with a computer-based system with thecapacity to capture, record, monitor, and identify biometric features ofa persons of interest.

BACKGROUND OF THE PRESENT INVENTION

In the 1993 film “The Fugitive”, actor Tommy Lee Jones famously relatedthe following quote: “[o]ur fugitive has been on the run for 90 minutes.Average foot speed over uneven ground, barring injuries, is 4miles-an-hour. That gives us a radius of six miles. What I want out ofeach and every one of you is a hard-target search of every gas station,residence, warehouse, farmhouse, henhouse, outhouse and doghouse in thatarea. Checkpoints go up at fifteen miles.” Whether the data quoted byMr. Jones is accurate or not, it is generally well known that in theevent of a prison escape, a robbery, a child abduction, a personreported missing, etc., time is very critical. The more time a personhas to get away, the larger the search area becomes. As the search areagrows, the price and cost of the search increases exponentially.

During the summer of 2015, two men escaped from an upstate New YorkPrison.

Initially, search dogs, helicopters, and hundreds of police officer andcorrections officers searched the wilderness and local communities,going house to house in neighborhoods. Two days after the fugitivesescaped, the State of New York offered a $100,000 reward for informationthat lead to the fugitives capture. One week into the search, the16-square-mile search area produced no results. It is reported that over1,000 police officers, Federal Bureau of Investigation (FBI) agents, andUnited States Marshalls assisted in the 23-day search. It is furtherreported that the manhunt cost the state approximately $23 milliondollars.

SUMMARY OF INVENTION

The present disclosure provides an improved subject monitoring system,comprising an unmanned aerial vehicle equipped with a global positioningsystem receiver capable of determining the location of the unmannedaerial vehicle, a microphone capable of capturing a voice sampleassociated with a monitored subject (or person), and a communicationsport capable of transmitting and receiving electronic data over acommunications medium. The subject monitoring system further includes acomputing system that can transmit and receive data to/from the unmannedaerial vehicle. As described herein, the computing system has a userinterface, a processor, and a number of modules implemented to controland perform various functionalities. For example, a steering module maybe used. The steering module may be configured to control the movementsof the unmanned aerial vehicle based on electronic data received at theuser interface. In an embodiment, a voice analysis module is used toauthenticate the identity of the monitored subject.

It is a further object of this disclosure to deploy an unmanned aerialvehicle, operate the UAV in accordance with the mode of operation of theUAV, determine whether a subject has been detected, capture a firstvoice sample associated with the subject, authenticate the identity ofthe subject, and transmit the GPS location of the unmanned aerialvehicle to a computing device.

The main objective of the present disclosure is to provide a UAV withthe capabilities of locating, identifying, and tracking a knowncriminal, fugitive, missing person, and/or any other person of interest,as well as providing general law enforcement support functions.

BRIEF DESCRIPTION OF THE DRAWINGS

A further understanding of the present disclosure can be obtained byreference to the preferred embodiment and alternate embodiments setforth in the illustrations of the accompanying drawings. Although theillustrated embodiments are merely exemplary of systems for carrying outthe present invention, both the organization and method of operation ofthe invention, in general, together with further objectives andadvantages thereof, may be more easily understood by reference to thedrawings and the following description. The drawings are not intended tolimit the scope of this disclosure, which is set forth withparticularity in the claims as appended or as subsequently amended, butmerely to clarify and exemplify the invention. For a more completeunderstanding of the present disclosure, reference is now made to thefollowing drawings in which:

FIG. 1 depicts a functional block diagram of an exemplary monitoringsystem;

FIGS. 2A-2B depict functional block diagrams of exemplary monitoringsystems;

FIG. 3 depicts a flow chart diagram of an exemplary method for locatinga person of interest, using a UAV;

FIG. 4 depicts a flow chart diagram of an exemplary method for locatingand tracking a person of interest, using a UAV;

FIG. 5 depicts an exemplary method for authenticating the identity of aperson of interest, using UAV;

FIGS. 6A-6B depict an exemplary methods for authenticating the identityof a person of interest, using a UAV;

FIG. 7 depicts an exemplary method for authenticating the identity of aperson of interest, using a UAV;

In the drawings, like reference numbers generally indicate identical orsimilar elements. Additionally, generally, the left-most digit(s) of areference number identifies the drawing in which the reference numberfirst appears.

DETAILED DESCRIPTION OF THE INVENTION

As required, a detailed illustrative embodiment of the present inventionis disclosed herein. However, techniques, systems and operatingstructures in accordance with the present disclosure may be embodied ina wide variety of forms and modes, some of which may be quite differentfrom those in the disclosed embodiment. Consequently, the specificstructural and functional details disclosed herein are merelyrepresentative, yet in that regard, they are deemed to afford the bestembodiment for purposes of disclosure and to provide a basis for theclaims herein, which define the scope of the present invention. Thefollowing presents a detailed description of a preferred embodiment aswell as alternate embodiments such as a simpler embodiment or morecomplex embodiments for alternate devices of the present invention.

An unmanned aerial vehicle (UAV) is an aircraft that may be manuallycontrolled at a remote location or can fly autonomously based onprogrammed flight. Currently, UAV's cannot verify or authenticate theidentity of a monitored subject such as a known criminal, fugitive,missing person, and/or any other person of interest.

In view of the foregoing, there exists a need for an improved method andapparatus for locating, identifying, and tracking a known criminal,fugitive, missing person, and/or any other person of interest.

FIG. 1 illustrates a functional block diagram of an exemplary monitoringsystem 100, useful for implementing various embodiments of the presentdisclosure. As depicted, an unmanned aerial vehicle (“UAV”) 102 is inelectronic communication with at least one computing system 118 overcommunications link 116. In an embodiment, the UAV 102 includes one ormore features to provide additional functionality. For example, the UAV102 may include, for example, global positioning system (“GPS”) receiver104, directional control system 106, microphone 108, camera 110, payloaddeployment system/mechanism 112, and communications port 114. Thecomputing system 118 likewise includes one or more features to provideadditional functionality. For example, computing system 118 may includeat least one processor 120, user interface 130, and memory 134. In anembodiment, the processor(s) may additionally include steering module122, voice analysis module 124, facial recognition module 126, andpayload deployment module 128. In an embodiment, user interface 130 mayfurther include user input/output device(s) 132.

For purposes of this discussion, the term “module” shall be understoodto include at least one of software, firmware, and hardware (such as oneor more circuit, microchip, processor, or device, or any combinationthereof), and any combination thereof. In addition, it will beunderstood that each module may include one, or more than one, componentwithin an actual device, and each component that forms a part of thedescribed module may function either cooperatively or independently ofany other component forming a part of the module. Conversely, multiplemodules described herein may represent a single component within anactual device. Further, components within a module may be in a singledevice or distributed among multiple devices in a wired or wirelessmanner. As such, one or more modules may be used alone (or incombination) to provide an improved systems and methods for locating,identifying, authenticating, and/or tracking the location and movementsof a law enforcement officer, search and rescue team member, a knowncriminal, fugitive, missing person, and/or any other person of interest.

UAV 102 is an unmanned aircraft that can fly autonomously, i.e., onauto-pilot, based on a pre-programmed flight pattern and/or that can becontrolled by a remote operator/pilot. In an embodiment, the UAV isflown semi-autonomously. In an embodiment, the UAV may be implemented asa helicopter having at least one rotor to lift and propel the aircraft,each rotor having a plurality of blades; a quad-copter, having fourrotors to lift and propel the aircraft; or any other type of unmannedflying machine capable of performing the methods described herein.

In an embodiment, the UAV includes GPS receiver 104. GPS receiver 104may be implemented using either global navigation satellite system(GNSS) type receivers or any other GPS receiver capable of providing theUAV's real-time location.

In an embodiment, UAV 102 further includes directional control system106.

Directional control system 106 can be implanted as circuitry, amicroprocessor, a processor, or any other means that can convert datasignals into an electronic signals that cause components of the UAV tolift, propel and steer the UAV. In an embodiment, direction controlsystem sends and receives data with GPS receiver 104 in order to direct,i.e., fly, the UAV to either a desired or pre-programmed location.Further, the direction control system sends and receives data withcommunications port 114. As will be discussed in greater detail below, aremote operator (or pilot) sends movement commands to the UAV throughcommunications port 114. Communications port 114 provides the commandsto the directional control system in order to fly the UAV to a desiredlocation.

In an embodiment UAV 102 further includes microphone 108. The microphone108 can be any of one or more of traditional microphones, a parabolicmicrophone, a laser Doppler vibrometer (LDV), or any other microphone orcombination of microphones capable of capturing voice signals. In anembodiment, microphone 108 further includes a cone, a parabolic dish, oris placed about a gimbal or a piezoelectric motor system. In suchembodiments the gimbal (and/or piezoelectric motor system) is programmedto point the microphone toward a desired subject. Alternatively, thegimbal (and/or piezoelectric motor system) is be controlled remotely byan operator (or pilot) through a communications port (such ascommunications port 114 of FIG. 1 ).

The microphone further includes an internal/embedded digital signalprocessor (DSP). The DSP may be programmed to perform audio signalanalysis, to automatically adjust gain control, to compensate forvariations in the level of incoming audio signals, to compress digitizedvoice data compression, to send and/or receive dual tone multi frequencysignals (DTMF) or in-band signaling, to monitor channel conditions andstatus, to detect presence of tones, and to detect silence/quiet.

In an embodiment UAV 102 further includes camera 110. The camera 110 maybe a digital camera capable of capturing facial images of a subject. Thecamera must provide images with a high enough quality, or definition, inorder to perform facial recognition tasks. In an embodiment, the cameraprovides still digital images. In alternative embodiments, the cameraprovides video. In yet additional embodiments, the camera provides areal-time video feed to an operator (or pilot) through a communicationsport 114. The camera may be secured to a gimbal and/or a piezoelectricmotor system. In such embodiments the gimbal (and/or piezoelectric motorsystem) may be programmed to point the camera toward a desired subjectin order to capture a facial image of the subject. Alternatively, thegimbal (and/or piezoelectric motor system) may be controlled remotely byan operator (or pilot) through the communications port. As shown, thecamera additionally exchanges data with GPS receiver 104. In suchembodiments the captured images further include metadata related to theGPS location of the photographed (or filmed) subject and/or the GPSlocation of the UAV while the images were captured.

In an embodiment, the camera may additionally comprises thermo-graphic,infrared, night-vision, and/or thermal imaging capabilities in order toidentify and/or authenticate the identity of an individual, such as alaw enforcement officer, a known criminal, fugitive, missing person,and/or any other person of interest.

In an embodiment, the camera may additionally comprise magnificationcapabilities, where the camera can automatically (or manually) zoom-inor zoom-out in order to obtain images of a person to identify and/orauthenticate the identity of an individual in the captured image.

In an embodiment, the camera further includes an image processor. Theimage processor may be programmed to perform image analysis, toautomatically adjust brightness, saturation, contrast, or other imagefeatures, to compensate for variations in lighting, definition,pixilation, etc. of varying between captured images, to compressimage/video files, to frame identifying features within an image/video,to decompress stored image data, to compress image, video, and/or livefeed data for playback, to adjust the rate/speed of video playback.

In an embodiment, UAV 102 further includes payload deploymentsystem/mechanism 112. Payload deployment system/mechanism 112 mayinclude circuitry, a microprocessor, processor or any other meanscapable of controlling the deployment of a payload. In an embodimentwhere the payload is a pressurized gas (such as pepper spray or teargas), the payload deployment system/mechanism includes a cavity designedto receive a pressurized gas canister, including any required mechanismfor controlling the release of the pressurized gas. In an embodimentwhere the payload is a projectile (such as rubber bullets, bean-bags, orother non-lethal ammunition) the payload delivery system includes asuitable gun, firearm, or launcher to project the ammunition toward adesired location. In an embodiment where the payload is a deployablecanister (such as tear gas, a flash canister, or pepper spray), thepayload delivery system may include releasable hooks, a releasable door,a sliding door, or any other means capable of releasing and/oractivating the payload. In embodiments where the payload is an aid kit,food, water, firearms, rope, or any other supply that may be needed, thepayload delivery system may include releasable hooks, a releasable door,a sliding door, or any other means capable of releasing the payload.

In an embodiment, the payload deployment system/mechanism (such aspayload deployment system/mechanism 112 of FIG. 1 ) is pre-programmed toactivate upon the occurrence of an event, when the UAV has reached adesired location, when the identity of a subject has been authenticated,or at the occurrence of any other foreseeable event commonly encounteredwhile chasing a known criminal, a fugitive, or when rescuing someone inneed. Further, the payload deployment system/mechanism may be activatedby an operator (or pilot) by sending a command to the payload deploymentsystem/mechanism through a communications port (such as communicationsport 114 of FIG. 1 ).

In an embodiment, the UAV further includes a speaker and/or flashinglights. In such embodiments, the speaker may be used to allow anoperator (or pilot) to communicate with the monitored subject. Further,the microphone may be used to attempt to bait, or entice, the monitoredsubject to speak, so a voice signal sample may be collected. Further,the speaker and/or the flashing lights may be used to catch theattention of the monitored subject in order to bait, or entice, themonitored subject to look at the camera, so a facial image may becollected.

In an embodiment, the UAV is equipped with a noise cancellation systemto cancel, attenuate, or eliminate any noise created by the operation ofthe UAV and/or the UAV propellers.

As depicted in FIG. 1 , UAV 102 is electronically coupled to computersystem 118 through communications link 116. In an embodiment,communications port 114 of UAV 102 sends/receives data acrosscommunications link 116 to/from communications port 115 of computersystem 118. A communications link (such as communications link 116 ofFIG. 1 ) may be implemented using at least one mobile or wirelesscommunications protocol, such as: long term evolution (LTE), Wi-Fi,Bluetooth, radio-frequency, first generation (1G) wireless technology,second generation (2G) wireless technology, third generation (3G)wireless technology, fourth generation (4G) wireless technology,code-division multiple access (CDMA), frequency division multiple access(FDMA), generic access network (GAN), global system for mobile (GSM), orany other wireless protocol capable of creating a communications linkbetween a UAV and at least one computer system. In an embodiment, thecommunications link is implemented using a wired connection. In suchembodiments, at least one computing system may be located onboard theUAV. In an alternative embodiment, the UAV may be tethered to at leastone computing system using a cable, wire, or other means for passingdata through a wired connection. Various example, non-limitingembodiments, of contemplated monitoring system configurations shall nowbe discussed.

As depicted in FIG. 1 , computing system 118 is implemented on a singledevice. As mentioned above, the computing system may include one of morefeatures to provide additional functionality. In an embodiment, thecomputing system may further include input/output device(s) 132, such asmonitors, keyboards, pointing devices, joysticks, throttles, buttons,wheels, touchscreens, graphical user interface buttons (GUI), etc., thatcommunicate with a processor through user interface 130.

A user interface (such as user interface 130 of FIG. 1 ) and applicableinput/output devices (such as input/output device(s) 132 of FIG. 1 ) maybe used to manually control various functional features of a monitoringsystem. For example, in an embodiment, a joystick is used to control thedirection, location, and/or movement of the UAV (such as UAV 102 of FIG.1 ). In an embodiment, a monitor is used to view images, video, or watcha live feed provided by a UAV. In an additional embodiment, atouchscreen is used to display authentication results provided by aprocessor.

In an embodiment, computing system 118 further includes memory 134.Memory 134 is implemented as a main or primary memory, such as randomaccess memory (RAM). Memory 134 may include one or more levels of cache.The memory may have stored therein control logic, such as computersoftware, and/or data. In additional embodiments, memory may alsoinclude one or more secondary storage devices or memory such as a harddisk drive and/or a removable storage device or drive. The removablestorage drive may include a floppy disk drive, a magnetic tape drive, acompact disk drive, and/or any other storage device/drive.

In an embodiment, the computing system further includes at least oneprocessor. As depicted in FIG. 1 , processor 120 further includessteering module 122, voice analysis module 124, facial recognitionmodule 126, payload deployment module 128, and/or any other modulenecessary to perform the functionality described herein. In additionalembodiments processor 120 includes only a single module or any modulescontemplated herein. Each module may be implemented as logic embodied insoftware, firmware, hardware, and/or operating system implementations inorder to perform or carry-out a desired function. Further, as usedherein, a module may also be implemented a collection of softwareinstructions. One or more software instructions in the modules may beembedded in firmware, such as in an erasable programmable read onlymemory (EPROM). The modules described herein may also be stored in anytype of non-transitory computer-readable medium or other storage device.

In an embodiment, the modules are incorporated using a single computingsystem and processor. In other embodiments, the modules are incorporatedusing more than one computing system and/or processor. Referring now toFIG. 2A, shown is non-limiting functional block diagram of monitoringsystem 200 a, useful for implementing various embodiments of the presentdisclosure. As shown, UAV 202 is in electronic communication withnetwork 219 through communications link 216. Network 219 may becomprised of computer systems 218 a-d, each having at least oneprocessor 220 a-d, respectively. The processors 220 a-d may send andreceive data to other processors within the network and/or the UAVthrough communications infrastructure 217. For example, in anembodiment, facial recognition module 226, located within computingsystem 218 c and processor 220 c, communicates with UAV 202 bytransmitting data through communications infrastructure 217 andcommunications link 216. In another non-limiting example, voice analysismodule 224 located within computing system 218 b and processor 220 b,sends and receives data with steering module 222 through communicationsinfrastructure 217.

A network (such as network 219 of FIG. 2A) may be implemented as a widearea network (WAN), a local area network (LAN), a metropolitan areanetwork (MAN), or any other network capable of performing thefunctionality described herein. As such, a communications infrastructure(such as communications infrastructure 217 of FIG. 2A) may be a wiredand/or wireless connection. Further, the communications infrastructuremay operate using a communications protocol such as: long term evolution(LTE), Wi-Fi, Bluetooth, radio-frequency, first generation (1G) wirelesstechnology, second generation (2G) wireless technology, third generation(3G) wireless technology, fourth generation (4G) wireless technology,code-division multiple access (CDMA), frequency division multiple access(FDMA), generic access network (GAN), global system for mobile (GSM), orany other network protocol capable of sending and receiving data betweennodes within a network and/or a UAV.

Referring now to FIG. 2B, shown is non-limiting functional block diagramof monitoring system 200 b, useful for implementing various embodimentsof the present disclosure. As shown, UAV 202 is in electroniccommunication with multiple computing systems 218 e-h overcommunications link 216, each computing system having at least oneprocessor 220 e-h therein.

As depicted in FIG. 2B, each processor 220 e-h contains one moduletherein. In other embodiments, however, a processor 120 may comprisemultiple modules. For example, a monitoring system may be implementedusing one computing system having multiple processors, each processorhaving at least one module therein. For example, in an embodiment wherethe monitoring system (such as monitoring system 100 of FIG. 1 ) onlyrequires a steering module and a voice analysis module, the steeringmodule may be implemented using a first computing system while the voiceanalysis module may be implemented using a second computing system. Inanother non-limiting embodiment, where the monitoring system onlyrequires a steering module, a facial recognition module, and a payloaddeployment, the steering module and payload deployment module areimplemented using a first computing system or processor while the facialrecognition module is implemented using a second computing system orprocessor. In an embodiment, where only one module is necessary, thatmodule may be implemented using a plurality of computing systems orprocessors, each acting as a node within a network.

Various example, non-limiting embodiments, of contemplated software,firmware, hardware, and/or operating system modules shall now bediscussed.

A steering module (such as steering module 122 of FIG. 1 or steeringmodule 222 of FIGS. 2A and 2B) may provide directional commands to aUAV. The steering module may perform directional commands, including:providing the UAV with real-time route and GPS coordinates, analyzing amap and providing the UAV with a desired auto-pilot travel route, and/oranalyzing geographic features of the area and providing instructions toensure the UAV avoids any nearby obstacles. In an embodiment, thesteering module performs directional commands in response to operator(or pilot) instructions received from input/output devices 132 through auser interface. The steering module may perform the directional commandsusing software, firmware, hardware, and/or operating systemimplementations.

Voice analysis module 124 and/or voice analysis module 224 may beimplemented to compare voice signals against stored voiceprints in orderto identify and/or authenticate the identity of a subject, such as acriminal, fugitive, missing person, and/or any other person of interest.Further, the voice analysis module may code captured voice signals intodigitized voice files (or voiceprints) for recording and use forauthentication. The voice analysis module may also decode user digitizedvoice files and convert the digital signals to audio signals forplayback. In an embodiment, the voice analysis module receives a voicesignal captured using a UAV, converts the capture voice signals into adigitized voice file, and compares the digitized voice signal againstvoiceprints stored in a voiceprint database in order to identify acriminal, fugitive, missing person, and/or any other person of interest.In an embodiment, the voiceprint database comprises at least one voicesignal sample of a subject along with the subject's identifyinginformation.

Voice analysis module 124 and/or voice analysis module 224 furtherincludes an internal/embedded digital signal processor (DSP). The DSPmay be programmed to perform audio signal analysis, to automaticallyadjust gain control, to compensate for variations in the level ofincoming audio signals, to compress digitized voice data compression, tosend and/or receive dual tone multi frequency signals (DTMF) or in-bandsignaling, to monitor channel conditions and status, to detect presenceof tones, detect silence/quiet, to decompress stored audio data, tocompress audio data for playback, to adjust the volume and rate of speedof playback, in order to identify and/or authenticate the voice of acriminal, fugitive, missing person, and/or any other person of interest.

In an embodiment, the voiceprint database comprises voice signal samplesprovided willingly by any subject, i.e., person, at any time. In anadditional embodiment, the voice signal sample may be provided by afamily member of the subject. For example, in an embodiment wheremonitoring system 100 or monitoring systems 200 a and 200 b is used tolocate and identify a missing person, voice signal samples of themissing person may be provided by friends and/or family members. In anembodiment, the voiceprint database may comprise voice signal samplesprovided by an inmate, a convicted criminal, or other family membersduring registration and/or any other time in order to identify and/orauthenticate the voiceprint of a criminal, fugitive, missing person,and/or any other person of interest. A national voice database may alsobe used to access voice signal samples of wanted criminals.

Upon storing a voice signal sample in the voiceprint database, the voiceanalysis module analyzes a characteristic of the voice signal data suchas, in one non-limiting example, the pitch (i.e., tonal quality) over aperiod of time. However, in other non-limiting examples, the voiceanalysis module may analyze duration, loudness, stress, emotion,mixed-frequencies, timbre, or other similar types of characteristics inthe voice data, or a combination of these characteristics. Based on ananalysis of these characteristics, the system generates a voiceprint—aunique biometric measurement of the person's voice—that can be comparedto other voiceprints to determine a statistical “match” for identifyinga person such as criminal, fugitive, missing person, and/or any otherperson of interest. In one example, the voice data of the speaker wouldbe measured and recorded after, for as few as 3-5 seconds.

Calculated voiceprints are stored in the voiceprint database. In anembodiment, to obtain a baseline pitch with which to compare, a subjectmight be required to read a script for a period of time duringregistration or other time so an average value of pitch could beestablished for future use. In an embodiment the voice sample files maybe stored in format where a user may replay the sample. In otherembodiments, only the extracted pitch, tonal quality, loudness, timbre,etc., may be stored as a voiceprint.

Digital voice sample files and/or voiceprint database may be stored inmemory 134. In another embodiment, however, the digital voice samplefiles and/or voiceprint database are stored anywhere accessible to themonitoring system, whether local or remote. The voice analysis modulemay perform its operations using software, firmware, hardware, and/oroperating system implementations.

Facial recognition module 126 and/or facial recognition module 226 areimplemented to compare an image of a subject's face, i.e., facial image,against stored images and/or faceprint data in order to identify and/orauthenticate the identity of a subject such as a criminal, fugitive,missing person, and/or any other person of interest. In an embodiment,the facial recognition module receives an image, video, or live feedcaptured using a UAV and compare the received image, video, or live feedagainst facial images stored in an image database. In an embodiment, theimage database comprises at least one facial image of a subject alongwith the subject's identifying information. For example, the imagedatabase

In an embodiment, the facial recognition module further includes animage processor. The image processor may be programmed to perform imageanalysis, to automatically adjust brightness, saturation, contrast, orother image features, to compensate for variations in lighting,definition, pixilation, etc. of varying between captured images, tocompress image/video files, to frame identifying features within animage/video, to decompress stored image data, to compress image, video,and/or live feed data for playback, and to adjust the rate/speed ofvideo playback in order identify and/or authenticate the facial image ofa criminal, fugitive, missing person, and/or any other person ofinterest.

In an embodiment, the image database comprises sample images taken of,or provided by, any subject at any time. In an embodiment, the imagesample may be provided by the family member of a subject. For example,in an embodiment where the monitoring system 100 or monitoring systems200 a and 200 b are used to locate and identify a missing person, imagesamples of the missing person may be provided by friends and/or familymembers. In an embodiment, the image database may comprise image samplestaken of an inmate, a convicted criminal, or other family members duringregistration and/or any other time. A national image database may alsobe used to access image samples of wanted criminals.

Upon storing an image sample in the image database, the facialrecognition module may analyze at least characteristic of the imagedata. For example, the facial recognition module may identify facialfeatures by extracting landmarks, or features, from an image of thesubject's face to create a faceprint. For example, the facialrecognition module may analyze the relative position, size, and/or shapeof the eyes, nose, cheekbones, and jaw. In another embodiment, thefacial recognition module may normalize and compress the facial imagedata, only saving the data in the image that is useful for facerecognition. In such embodiments, an image provided by the UAV may thenthen compared with the stored facial data in order to identify and/orauthenticate the facial image of a criminal, fugitive, missing person,and/or any other person of interest.

The facial recognition module may be implemented as: a geometric system,which looks at distinguishing features; as a photometric system, whichis a statistical approach that distills an image into values andcompares the values with templates to eliminate variances; as a3-dimensional system, which uses 3D sensors to capture information aboutthe shape of a face, including distinctive features on the surface of aface, such as the contour of the eye sockets, nose, and chin; or as askin texture system, which turns the unique lines, patterns, and spotsapparent in a person's skin into a mathematical space. Further, thefacial recognition module employs any combination of theseimplementations.

Image/video files and/or image database may be stored in memory (such asmemory 134 of FIG. 1 ). In another embodiment, however, the image samplefiles and/or image database may be stored anywhere accessible to themonitoring system (such as monitoring system 100 of FIG. 1 or monitoringsystems 200 a and 200 b of FIGS. 2A and 2B, respectively), whether localor remote. The facial recognition module may perform its operationsusing software, firmware, hardware, and/or operating systemimplementations.

Payload deployment module 128 and/or payload deployment module 228provides payload deployment commands to the UAV. The payload deploymentmodule may perform commands, including: providing the UAV with real-timepayload deployment commands, providing the UAV with pre-programmedpayload deployment commands, and/or providing the UAV with situationalpayload deployment commands based on the occurrence of an event. Thesteering module may perform payload deployment commands in response tooperator (or pilot) instructions received from input/output devices(such as input/output devices 132 of FIG. 1 ). The payload deploymentmodule may perform the payload deployment commands using software,firmware, hardware, and/or operating system implementations.

Various example, non-limiting embodiments, of contemplated monitoringsystem methods shall now be discussed.

FIG. 3 illustrates method 300, a method for locating a person ofinterest, using a UAV. At step 340, the UAV is deployed. The UAV may bedeployed by launching the UAV and/or preparing to launch the UAV.

At step 342, it is determined whether the UAV is in auto-pilot mode orwhether it is in manual operation mode. If the UAV is in auto-pilotmode, at step 346, the UAV follows a received pre-programmed auto-pilotflight path. As mentioned above, the auto-pilot flight path may includegeographic obstacles that the UAV must negotiate around. Additionally,the auto-pilot flight path may include a “swath” path, where the UAVwill fly in pre-determined lines in order to fly over a specific plot ofland. At any time, an operator may interrupt the auto-pilot flight andbegin operating the UAV in manual operation mode (not illustrated inFIG. 3 ). For example, when the UAV is flying in auto-pilot mode and anoperator would like to observe something from a different distance,angle, or for a longer period of time, he or she may take control of theUAV. In an embodiment, the pilot may press a button or sequence ofbuttons to initialize a new pre-programmed flight maneuver. Further, theoperator (or pilot) may modify the programmed flight path at any timeduring operation. At any time, the operator may return the UAV toauto-pilot mode and the UAV returns to the GPS location where theoperator interruption took place and resume the predetermined flightpath.

Now returning to step 342. If at step 342, the UAV has been deployed inmanual operation mode, the operator controls of the UAV. At step 350,the operator (or pilot) controls the movements of the UAV usinginput/output devices (such as input/output device(s) 132 of FIG. 1 )through a user interface (such as user interface 130 of FIG. 1 ). In anembodiment, the operator may manually control every single movement. Inan additional embodiment, the operator may control movements byselecting buttons that correspond to preprogrammed maneuvers, such as:change altitude, change speed, go to a desired longitude and/orlatitude, return “home”, and more.

At step 348, based on observed data, the UAV and/or a computing system(such as computing system 118 of FIG. 1 ) determines whether a potentialsubject, i.e., human, has been detected. The UAV continues flying untila potential subject has been detected. In an embodiment, components onboard the UAV continuously transmit signals to the computing system. Asnoises and/or images are captured using microphone(s) and/or camera(s)onboard the UAV, the system continuously monitors for sounds and imagesthat indicate the presence of a human (or potential subject).

When it is determined that a potential subject has been located, at step352 the UAV attempts to capture an audio signal of the monitored subjectusing an onboard microphone (such as microphone 108 of FIG. 1 ).

At step 354, the voice analysis module, located within the processor,attempts to authenticate an identity of the monitored subject, asdescribed above. For example, the voice analysis module compares thecaptured voiceprint against the voiceprint database in order to identifyand/or authenticate the voice of a criminal, fugitive, missing person,and/or any other person of interest. If the identity of the monitoredsubject is not authenticated, subject monitoring method 300 returns tostep 342. If the identity of the monitored subject is authenticated, atstep 356 the UAV transmits either the current GPS coordinates of the UAVor estimated GPS coordinates of the monitored subject, i.e., theidentified criminal, fugitive, missing person, and/or any other personof interest based on the GPS coordinates of the UAV. At step 358, apayload carried on board the UAV is deployed.

In an embodiment, the estimated GPS coordinates of the monitored subjectare determined/estimated based on the GPS coordinates of the UAV and atleast one other data point. Additional data points may include, forexample: camera angle, camera direction, camera zoom, measured voicesignal strength, triangulated coordinates based on the UAV position andother geographic features in the surrounding area, digital maps havingGPS coordinates, or sonar pulses. In an embodiment, the estimated GPScoordinates of the monitored subject are determined after receiving, ata computing system, the GPS coordinates of the UAV and the angle,direction, and zoom of camera used to capture a facial image of themonitored subject. The computing system compares the received dataagainst GPS coordinates associated with the general geographic locationusing a map to estimate the monitored subject's location. In anadditional embodiment, the estimated GPS coordinates may be calculatedon board the UAV.

FIG. 4 illustrates method 400, a method for locating and tracking aperson of interest, using a UVA. At step 440, the UAV is deployed. Asdescribed above, the UAV may be deployed by launching the UAV and/orpreparing to launch the UAV.

At step 442, it is determined whether the UAV is in auto-pilot mode orwhether it is in manual operation mode. If the UAV is in auto-pilotmode, at step 444, the UAV follows a received pre-programmed auto-pilotflight path. As mentioned above, the auto-pilot flight path may includegeographic obstacles that the UAV must negotiate around. Additionally,the auto-pilot flight path may include a “swath” path, where the UAVwill fly in pre-determined lines in order to fly over a specific plot ofland. At any time, an operator may interrupt the auto-pilot flight andbegin operating the UAV in manual operation mode (not illustrated inFIG. 4 ). For example, when the UAV is flying in auto-pilot mode and anoperator would like to observe something from a different distance,angle, or for a longer period of time, he or she may take control of theUAV. In an embodiment, the pilot may press a button or sequence ofbuttons to initialize a new pre-programmed flight maneuver. Further, theoperator (or pilot) may modify the programmed flight path at any timeduring operation. At any time, the operator may return the UAV toauto-pilot mode and the UAV returns to the GPS location where theoperator interruption took place and resume the predetermined flightpath.

Now returning to step 442. If at step 442, the UAV has been deployed inmanual operation mode, the operator controls of the UAV. At step 450,the operator (or pilot) controls the movements of the UAV usinginput/output devices through the user interface.

At step 448, based on observed data, the UAV and/or a computing systemdetermines whether a potential subject, i.e., human, has been detected.

When it is determined that a potential subject has been located, at step451 the UAV attempts to capture an image, video, and/or live feed of themonitored subject using an onboard camera (such as camera 110 of FIG. 1). At step 453, the facial recognition module, located within the,determines whether the captured image is of sufficient quality in orderto authenticate the monitored subject's identity. If the captured image,video, or live feed does not meet the quality needed, at step 455 theUAV may be repositioned and additional mechanisms such as flashinglights and/or noised may be used to entice the monitored subject to lookat the UAV. Subject monitoring method 400 then returns to step 451.

If at step 453 it is determined that the image, video, and/or live feedis sufficient, the facial recognition module attempted to authenticatean identity of the monitored subject, as described above. For examplethe facial recognition module may identify and/or authenticated thefacial image of a criminal, fugitive, missing person, and/or any otherperson of interest by comparing the captured image(s) against storedimages. If the identity of the monitored subject is not authenticated,subject monitoring method 400 returns to step 342. If at step 453 theidentity of the monitored subject is authenticated, at step 456 the UAVtransmits the estimated GPS coordinates of the monitored subject. In anembodiment not shown, at step 456, the UAV may alternatively transmitthe current GPS coordinates of the UAV. At step 460, the UAV tracks themovements of the identified monitored subject and continues to transmitthe updated coordinate estimates of the monitored subject as he/shemoves relative to the UAV. In an embodiment the UAV transmits theupdated coordinates continuously. In an additional embodiment the UAVtransmits the updated coordinates at pre-determined intervals. In anembodiment, the UAV transmits the current GPS coordinates of the UAV asit tracks the monitored subject.

Various example, non-limiting embodiments, of contemplated monitoringsystem implementations shall now be discussed.

FIG. 5 illustrates a method for authenticating the identity of a personaof interest 500, useful for illustrating various embodiments of thepresent disclosure.

As illustrated in FIG. 5 , UAV 502 is controlled by operator 565 usinginput/output devices (not labeled) on user interface 530 b overcommunications link 516. Monitored subject 564 a, i.e., person ofinterest, is traversing geographic terrain 568. As illustrated,monitored subject 564 a may be a search and rescue team member, afugitive, a known criminal, a law enforcement officer in need ofsupplies, a missing person, a person of interest, a kidnapped child, orany other person. As the monitored subject traverses the terrain, theUAV captures a facial image of monitored subject as well as voicesignals 562 a.

Upon capturing the images and voice signals, UAV 502 transmits thecaptured data to a computing system (not labeled) and a correspondingprocessor (not labeled) over communications link 516.

A facial recognition module (such as facial recognition module 126 ofFIG. 1 or facial recognition module 226 of FIGS. 2A and 2B) analyzescaptured image 564 b (or faceprint), while the captured image isdisplayed on user interface 530 a. A voice analysis module (such asvoice analysis module 124 of FIG. 1 or facial recognition module 224 ofFIGS. 2A and 2B) converts the captured voice signals into digital filesand analyze digital voice signals 562 b (or voiceprints), while thevoice signal analysis is displayed on user interface 530 b.

FIG. 6A illustrates a method for authenticating the identity of apersona of interest 600, useful for illustrating various embodiments ofthe present disclosure.

As illustrated in FIG. 6A, operator 665 controls UAV 602 with userinterface 630 b over communications link 616. As illustrated, monitoredsubject 670 a may be a fugitive, a known criminal, a law enforcementofficer in need of supplies, a missing person, a person of interest, akidnapped child, an injured rescuer, and injured hiker, or any otherperson. As the monitored subject lies on the terrain, the UAV captures afacial image of monitored subject as well as voice signals 662 a.Further illustrated, the UAV broadcasts voice signals 672. Voice signals672 may include: a voice message from the operator (or pilot), apre-recorded message requesting the monitored subject turn him orherself in to the authorities, a conversation taking place between theoperator and the monitored subject, or any other audio signalappropriate for the occasion. For example, in an embodiment where themonitored subject 670 is a law enforcement officer seeking additionalsupplies (such as more ammunition, a firearm, etc.) the UAV may ask themonitored subject specific questions and/or require a voiceprintpassword in order to authenticate the identity of the subject before,for example, deploying the payload, i.e., ammunition, firearm, etc.

Upon capturing the images and voice signals, UAV 602 transmits thecaptured data to a computing system (not labeled) and a correspondingprocessor (not labeled) over communications link 616.

FIG. 6B illustrates a method for authenticating the identity of apersona of interest 630 b, useful for illustrating various embodimentsof the present disclosure. User interface 630 b comprises a number ofinput/output devices 632 for controlling various functional features ofa monitoring system. For example, in an embodiment, a joystick is usedto control the direction, location, and/or movement of the UAV.

Facial recognition module 126 or facial recognition module 226 analyzecaptured image 664 b, while user interface 630 b displays the capturedimage.

Voice analysis module 124 or voice module 224 converts the capturedvoice signals into digital files (and/or voiceprints) and analyzedigital voice signals 662 b, while the user interface 530 b displays thevoice signal analysis.

As illustrated in FIG. 7 , operator 765 controls UAV 702 usinginput/output devices (not labeled) on user interface 730 b overcommunications link 716. As illustrated, monitored subjects 776 mayinclude: inmates fighting in the prison yard, known criminals engagingin a drug exchange, or any other suspicious activity. As the monitoredsubjects engage in the suspicious behavior, the UAV captures a facialimage of monitored subject as well as voice signals.

Upon capturing the images and voice signals, UAV 702 transmits thecaptured data to a computing system (not labeled) and a correspondingprocessor (not labeled) over communications link 716. At the occurrenceof a detected event, or at the command of the operator (or pilot), thepayload deployment module causes the UAV to deploy an onboard payload.As illustrated, the payload may be pepper spray or tear gas. In otherembodiments, where the payload is a projectile (such as rubber bullets,bean-bags, or other non-lethal ammunition) the UAV may fire theprojectile toward monitored subjects 776. In an embodiment where thepayload is a deployable canister (such as tear gas, a flash canister, orpepper spray), the UAV may release and/or activate at, or near,monitored subjects 776.

It is to be appreciated that the Detailed Description section, and notthe Summary and Abstract sections (if any), is intended to be used tointerpret the claims. The Summary and Abstract sections (if any) may setforth one or more but not all exemplary embodiments of the invention ascontemplated by the inventor(s), and thus, are not intended to limit theinvention or the appended claims in any way.

While the invention has been described herein with reference toexemplary embodiments for exemplary fields and applications, it shouldbe understood that the invention is not limited thereto. Otherembodiments and modifications thereto are possible, and are within thescope and spirit of the invention. For example, and without limiting thegenerality of this paragraph, embodiments are not limited to thesoftware, hardware, firmware, and/or entities illustrated in the figuresand/or described herein. Further, embodiments (whether or not explicitlydescribed herein) have significant utility to fields and applicationsbeyond the examples described herein.

Embodiments have been described herein with the aid of functionalbuilding blocks illustrating the implementation of specified functionsand relationships thereof. The boundaries of these functional buildingblocks have been arbitrarily defined herein for the convenience of thedescription. Alternate boundaries can be defined as long as thespecified functions and relationships (or equivalents thereof) areappropriately performed. Also, alternative embodiments may performfunctional blocks, steps, operations, methods, etc. using orderingsdifferent than those described herein.

References herein to “one embodiment,” “an embodiment,” “an exampleembodiment,” or similar phrases, indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it would be within the knowledge of persons skilled in therelevant art(s) to incorporate such feature, structure, orcharacteristic into other embodiments whether or not explicitlymentioned or described herein.

The breadth and scope of the invention should not be limited by any ofthe above-described exemplary embodiments, but should be defined only inaccordance with the following claims and their equivalents.

What is claimed is:
 1. An unmanned aerial vehicle, comprising: a globalpositioning system receiver configured to determine a first globalposition of the unmanned aerial vehicle; a flashing light source; abiometric sensing device; and a processor in communication with theglobal positioning system receiver and the biometric sensing device,wherein the processor is configured to: cause the unmanned aerialvehicle to fly a flight path until a potential subject is detected;determine that a quality of previously captured video is not sufficientto authenticate the potential subject; cause the flashing light sourceto output light in response to the determination that the quality ofpreviously captured video is not sufficient to authenticate thepotential subject; capture, responsive to causing the flashing lightsource to output light, biometric data associated with the potentialsubject using the biometric sensing device; responsive to authenticatingthe potential subject as a monitored subject based on the biometricdata: transmit the first global position of the unmanned aerial vehicleto a computing device; receive a response from the computing device;after receiving the response from the computing device, provide anestimated second global position of the monitored subject based on thefirst global position of the unmanned aerial vehicle and one of a datapoint associated with the biometric sensing device or a data pointassociated with the biometric data; continuously update the estimatedsecond global position of the monitored subject; and continuouslytransmit the estimated second global position of the monitored subjectto the computing device; and responsive to not authenticating thepotential subject as the monitored subject based on the biometric data,continue to cause the unmanned aerial vehicle to fly the flight path. 2.The unmanned aerial vehicle of claim 1, further comprising a microphone,wherein the biometric data is a voice sample captured by the microphone.3. The unmanned aerial vehicle of claim 1, wherein the biometric data isa facial image captured by a camera.
 4. The unmanned aerial vehicle ofclaim 1, wherein the response received from the computing devicecomprises an identity confirmation.
 5. The unmanned aerial vehicle ofclaim 1, wherein the processor is further configured to: determinewhether the monitored subject is moving.
 6. The unmanned aerial vehicleof claim 1, wherein the data point associated with the biometric sensingdevice comprises any one of a camera angle, a camera direction, and acamera zoom and the data point associated with the biometric datacomprises a measured voice signal strength.
 7. The unmanned aerialvehicle of claim 1, further comprising a noise cancellation system,wherein the noise cancellation system at least attenuates noisegenerated by the unmanned aerial vehicle.
 8. The unmanned aerial vehicleof claim 1, wherein the flight path comprises a pre-programmedauto-pilot path, the pre-programmed auto-pilot path including geographicobstacles.
 9. The unmanned aerial vehicle of claim 8, wherein theprocessor is further configured to allow at least one of manualoperation of the unmanned aerial vehicle and modification of thepre-programmed auto-pilot path during a flying of the unmanned aerialvehicle according to the pre-programmed auto-pilot path.
 10. A methodfor determining, by an unmanned aerial vehicle, a position of amonitored subject, the method comprising: causing the unmanned aerialvehicle to fly a flight path until a potential subject is detected;determining that a quality of previously captured video is notsufficient to authenticate the potential subject; causing a flashinglight source of the unmanned aerial vehicle to output light in responseto the determination that the quality of previously captured video isnot sufficient to authenticate the potential subject; capturing,responsive to causing the flashing light source to output light,biometric data associated with the potential subject; and responsive toauthenticating the potential subject as the monitored subject based onthe biometric data: transmitting, based on authenticating an identity ofthe potential subject, a first global position of the unmanned aerialvehicle to a computing device; after transmitting the first globalposition of the unmanned aerial vehicle: providing an estimated secondglobal position of the monitored subject based on the first globalposition of the unmanned aerial vehicle and one of a data pointassociated with the biometric sensing device or a data point associatedwith the biometric data; continuously updating the estimated secondglobal position of the monitored subject; and continuously transmittingthe estimated second global position of the monitored subject to thecomputing device.
 11. The method of claim 10, wherein the potentialsubject is detected by: receiving a first piece of biometric data and asecond piece of biometric data captured using at least one of a cameraand a microphone of the unmanned aerial vehicle.
 12. The method of claim11, further comprising: attenuating, by a noise cancellation system ofthe unmanned aerial vehicle, noise generated by the unmanned aerialvehicle.
 13. The method of claim 10, wherein authentication of theidentity of the potential subject comprises: capturing a first piece ofbiometric data associated with the monitored subject; in response todetermining that the first piece of biometric data not meeting a qualityrequirement, repositioning the unmanned aerial vehicle; responsive torepositioning the unmanned aerial vehicle, capturing a second piece ofbiometric data associated with the monitored subject; and determining anidentity of the monitored subject based on the second piece of biometricdata.
 14. The method of claim 13, wherein the first piece of biometricdata and the second piece of biometric data includes at least one of avoice sample captured by a microphone and a facial image captured by acamera.
 15. The method of claim 13, wherein authentication of theidentity of the potential subject is based on analyzing the first pieceof biometric data and the second piece of biometric data.
 16. The methodof claim 13, wherein determining the identity of the monitored subjectcomprises capturing at least one of a thermo-graphic image, an infraredimage, a night-vision image, and a thermal image.
 17. The method ofclaim 16, further comprising automatically magnifying captured images ofthe monitored subject for identifying the monitored subject.
 18. Themethod of claim 10, further comprising: wherein the flight pathcomprises a pre-programmed auto-pilot path, the pre-programmedauto-pilot path including geographic obstacles.
 19. A non-transitorycomputer-readable medium having instructions stored therein, which whenexecuted by a processor in an unmanned aerial vehicle cause theprocessor to perform operations, the operations comprising: causing theunmanned aerial vehicle to fly a flight path until a potential subjectis detected; determining that a quality of previously captured video isnot sufficient to authenticate the potential subject; causing a flashinglight source to output light in response to the determination that thequality of previously captured video is not sufficient to authenticatethe potential subject; capturing, responsive to causing the flashinglight source to output light, biometric data associated with thepotential subject using a biometric sensing device; responsive toauthenticating the potential subject as a monitored subject based on thebiometric data: transmitting a first global position of an unmannedaerial vehicle to a computing device; receiving a response from thecomputing device; after receiving the response, providing an estimatedsecond global position of the monitored subject based on the firstglobal position of the unmanned aerial vehicle and one of a data pointassociated with the biometric sensing device or a data point associatedwith the biometric data; continuously updating a current position of theunmanned aerial vehicle; continuously updating the estimated secondglobal position of the monitored subject based on the current positionof the unmanned aerial vehicle; and continuously transmitting theestimated second global position of the monitored subject to thecomputing device; and responsive to not authenticating the potentialsubject as the monitored subject based on the biometric data, continuingto cause the unmanned aerial vehicle to fly the flight path.